deep network designer toolbox  (MathWorks Inc)

Journal: Pharmaceutics

Article Title: Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy

doi: 10.3390/pharmaceutics17030290

Figure Lengend Snippet: List of companies using AI and ML technologies in pharmaceutical research as discussed by [ 102 , 103 , 104 ].

Article Snippet: 2 , Molecular Discovery , Deep learning platform for structure-based drug design , AtomWise.

Techniques: Mutagenesis, Drug discovery, Software, Selection, Clinical Proteomics

Journal: eLife

Article Title: Discovery and biological evaluation of a potent small molecule CRM1 inhibitor for its selective ablation of extranodal NK/T cell lymphoma

doi: 10.7554/eLife.80625

Figure Lengend Snippet: ( A ) The identification of ten commercial-accessible aromatic fragments aided by deep reinforcement learning model; ( B ) Synthesis of LFS-1107 via the installation of aromatic tetrazole moiety selected from the previous step to the sulforaphene parent structure; ( C ) Assessment of protein-ligand binding kinetics and binding affinity of tetrazole aromatic fragments via Bio-layer interferometry (BLI) assay; ( D ) Binding affinity of LFS-1107 and KPT-330 determined via BLI assay: LFS-1107, K d ~1.25E-11 M; KPT-330: K d ~5.29E-09 M. Figure 1—source data 1. The chemical structure of 10 commercial-accessible aromatic fragments. Figure 1—source data 2. The synthesis of compound LFS-1107. Figure 1—source data 3. The data of affinities and binding kinetics of CRM1 to S5 and S8. Figure 1—source data 4. The data of affinities and binding kinetics of CRM1 to LFS-1107 and KPT-330.

Article Snippet: In the present study, we adopted the deep reinforcement learning based molecular de novo design method developed by Olivecrona etc. from AstraZeneca.

Techniques: Ligand Binding Assay, Binding Assay